Artikel
Planning and analyzing clinical trials with hierarchical composite endpoints: applications in heart failure
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Autoren
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Tobias Mütze
- Novartis Pharma AG, Basel, Switzerland
| Veröffentlicht: | 26. Februar 2021 |
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Gliederung
Text
Composite endpoints are commonly considered for the primary efficacy analysis in clinical trials in heart failure. The advantages of composite endpoints are multifold and include the increased statistical efficiency to detect differences between treatments, and the avoidance of competing risks and multiplicity adjustments. Examples of composite endpoints commonly considered in clinical trials in heart failure include the time to the composite of cardiovascular (CV) death or first heart failure hospitalization , and the composite events of cardiovascular death and (first and recurrent) heart failure hospitalizations. These composites are analyzed using time-to-event or recurrent event models. Recently, there has been an interest in studying endpoints that include symptom scores or biomarkers in addition to CV events and to account for the clinical importance of each component during the analysis [1], [2], [3], [4]. Finkelstein and Schoenfeld [5], Felker et al. [6], [7], and Pocock et al. [8] proposed methods to analyze the endpoints through ranking or pairwise comparison of every participant in the treatment arm to every participant in the control arm. In this presentation, we look at challenges and opportunities of analyzing hierarchical composite endpoints based on methods involving pairwise comparison. In particular, we focus on the effects of censoring on the pairwise comparisons, the impact of ties on the effect measure, and efficiency gains compared to traditional methods for CV events. Moreover, we discuss sample size considerations for a clinical trial with a hierarchical composite endpoint, illustrated by the Entresto study PARACHUTE-HF [2].
The authors declare that they have no competing interests.
The authors declare that an ethics committee vote is not required.
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